Calipsocean meeting
05/03/2024
As in Wang et al., 2023:
temperature
silicate
oxygen
NPP → Zeu
DIP, DIC, ALK, DOC
UVP5 dataset: 2876 profiles
Function diversity metrics (Magneville et al. 2022)
→ morphological diversity metrics (Beck et al., 2023)
morphological richness
morphological divergence
morphological evenness
…
Coming soon (no plankton trophic database to my knowledge).
Trophic status of a copepod?
Other dataset? ↑ taxonomic resolution but ↓ coverage.
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468 data points
Learning* VS test set, stratified by POC.
What about spatial & temporal autocorrelation?
Response variable:
uni- or multivariate
~normally distributed → log(POC)
Flexibility for predictors, handles interactions.
Complex & non-linear relationships.
Easy interpretation & implementation.
POC ~ temperature + silicate + Zeu + oxygen
R² = 81.6%
Good prediction!
POC ~ all plankton metrics
R² = 49.5%
OK prediction!
Best predictors:
ta. evenness
ta. diversity
mo. richness
POC ~ ta_eve + ta_div + mo_ric
R² = 46.0%
OK prediction!
ta_eve + ta_div + mo_ric ~ temperature + silicate + Zeu + oxygen
Mult. R² = 41.8%
OK prediction!
POC_res ~ ta_eve_res + ta_div_res + mo_ric_res
R² = 1.2%
Bad prediction!